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Langgraph Jobs in Augusta, GA (NOW HIRING)

Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) - enough to collaborate effectively, not lead * Experience with Jupyter, Docker, MLflow, or FastAPI * Front‑end ...

Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively, not lead* Experience with Jupyter, Docker, MLflow, or FastAPI* Front-end / dashboard ...

Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively, not lead * Experience with Jupyter, Docker, MLflow, or FastAPI * Front-end / ...

Langgraph information

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What job categories do people searching Langgraph jobs in Augusta, GA look for?

The top searched job categories for Langgraph jobs in Augusta, GA are:

What cities near Augusta, GA are hiring for Langgraph jobs?

Cities near Augusta, GA with the most Langgraph job openings:

Infographic showing various Langgraph job openings in Augusta, GA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Machine Learning Engineer

KSB GIW, Inc.

Grovetown, GA • On-site

$70 - $110/hr

Other

Posted 5 days ago


Job description

Machine Learning Engineer

Department: Engineering, Research & Development

Reports to: Metallurgical and Materials R&D Lab Manager

Location: Grovetown, GA, USA (onsite)

Shift: First

FLSA Status: Salary Exempt

Overview

Our R&D group is expanding its use of machine learning to solve real engineering problems, and we’re looking for a sharp, hands‑on early‑career engineer to join the team. You’ll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them.

The role lives where machine learning meets scientific computing: surrogate modeling, data‑driven approximations of physical systems, and ML models that respect the underlying engineering principles. You’ll build the data foundation that powers this work, implement and train models that bridge physics‑based simulation with modern machine learning, and work closely with an experienced technical lead who will guide your growth across data engineering, scientific ML, and emerging AI tooling.

Responsibilities
  • Build and maintain the data foundation: ingestion, cleaning, transformation, validation, and metadata standards
  • Implement and train machine learning models using Python and modern frameworks (PyTorch)
  • Contribute to applied AI tooling that supports the broader R&D workflow
  • Develop visualization and dashboard interfaces that present results to end users
  • Run experiments, track results, and report findings against defined targets
  • Help bring prototype code to production quality: testing, documentation, version control
  • Collaborate with team members across engineering disciplines
Qualifications
  • Education: Bachelor’s degree required; master’s preferred in Computer Science, Engineering, Applied Math, Physics, or a related field
  • Experience: 1–3 years of professional or substantial project experience in machine learning, data engineering, or scientific computing
  • Skills / Competencies:
    • Solid Python skills with hands‑on experience using core libraries: Machine learning (PyTorch, scikit‑learn), Data (NumPy, pandas), Scientific computing (SciPy, Matplotlib)
    • Foundational understanding of scientific computing: numerical methods, simulation concepts, or modeling of physical systems
    • Foundational understanding of neural networks, model training, and optimization
    • Experience with version control (Git) and working in a Linux environment
    • Strong written and verbal communication skills
    • Collaborative, coachable attitude
  • Preferred:
    • Experience building and maintaining data pipelines, metadata schemas, and data quality frameworks
    • Exposure to scientific / physics‑informed machine learning (surrogate modeling, embedding physical constraints into ML models)
    • Background in CFD, simulation, computational mechanics, or applied physics
    • Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) – enough to collaborate effectively, not lead
    • Experience with Jupyter, Docker, MLflow, or FastAPI
    • Front‑end / dashboard development experience (React)
    • Cloud compute (AWS or Azure) and GPU‑based training
    • Coursework or research projects in numerical methods, engineering, or applied science
Physical Requirements

Primarily desk‑type duty.

KSB Group is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

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